Effect of chronic exercise on appetite control in overweight and obese individuals

Purpose: The effect of exercise on body mass is likely to be partially mediated through changes in appetite control. However, no studies have examined the effect of chronic exercise on obestatin and cholecystokinin (CCK) plasma concentrations or the sensitivity to detect differences in preload energy in obese individuals. The objective of this study was to investigate the effects of chronic exercise on 1) fasting and postprandial plasma concentrations of obestatin, CCK, leptin, and glucose insulinotropic peptide (GIP) and 2) the accuracy of energy compensation in response to covert preload manipulation. Methods: This study used a 12-wk supervised exercise program in 22 sedentary overweight/obese individuals. Fasting/postprandial plasma concentrations of obestatin, CCK, leptin, and GIP were assessed before and after the intervention. Energy compensation at a 30-min test meal after a high-energy (607 kcal) or a low-energy (246 kcal) preload and for the rest of the day (cumulative energy intake [EI]) was also measured. Results: There was a significant reduction in the plasma concentration of fasting plasma GIP and both fasting and postprandial leptin concentrations after the exercise intervention (P < 0.05 for all). No significant changes were observed for CCK or obestatin. A significant preload–exercise interaction (P = 0.011) was observed on cumulative EI and energy compensation for the same period (−87% ± 196% vs 68% ± 165%, P = 0.011). Weight loss (3.5 ± 1.4 kg, P < 0.0001) was not correlated with changes in energy compensation. Conclusions: This study suggests that exercise improves the accuracy of compensation for previous EI, independent of weight loss. Unexpectedly, and in contrast to GIP and leptin, exercise-induced weight loss had no effect on obestatin or CCK concentrations.

A trusted ecosystem for Android applications based on context-aware access control

Private data stored on smartphones is a precious target for malware attacks. A constantly changing environment, e.g. switching network connections, can cause unpredictable threats, and require an adaptive approach to access control. Context-based access control is using dynamic environmental information, including it into access decisions. We propose an "ecosystem-in-an-ecosystem" which acts as a secure container for trusted software aiming at enterprise scenarios where users are allowed to use private devices. We have implemented a proof-of-concept prototype for an access control framework that processes changes to low-level sensors and semantically enriches them, adapting access control policies to the current context. This allows the user or the administrator to maintain fine-grained control over resource usage by compliant applications. Hence, resources local to the trusted container remain under control of the enterprise policy. Our results show that context-based access control can be done on smartphones without major performance impact.

Approaches to access control under uncertainty

The ultimate goal of an access control system is to allocate each user the precise level of access they need to complete their job - no more and no less. This proves to be challenging in an organisational setting. On one hand employees need enough access to the organisation’s resources in order to perform their jobs and on the other hand more access will bring about an increasing risk of misuse - either intentionally, where an employee uses the access for personal benefit, or unintentionally, through carelessness or being socially engineered to give access to an adversary. This thesis investigates issues of existing approaches to access control in allocating optimal level of access to users and proposes solutions in the form of new access control models. These issues are most evident when uncertainty surrounding users’ access needs, incentive to misuse and accountability are considered, hence the title of the thesis. We first analyse access control in environments where the administrator is unable to identify the users who may need access to resources. To resolve this uncertainty an administrative model with delegation support is proposed. Further, a detailed technical enforcement mechanism is introduced to ensure delegated resources cannot be misused. Then we explicitly consider that users are self-interested and capable of misusing resources if they choose to. We propose a novel game theoretic access control model to reason about and influence the factors that may affect users’ incentive to misuse. Next we study access control in environments where neither users’ access needs can be predicted nor they can be held accountable for misuse. It is shown that by allocating budget to users, a virtual currency through which they can pay for the resources they deem necessary, the need for a precise pre-allocation of permissions can be relaxed. The budget also imposes an upper-bound on users’ ability to misuse. A generalised budget allocation function is proposed and it is shown that given the context information the optimal level of budget for users can always be numerically determined. Finally, Role Based Access Control (RBAC) model is analysed under the explicit assumption of administrators’ uncertainty about self-interested users’ access needs and their incentives to misuse. A novel Budget-oriented Role Based Access Control (B-RBAC) model is proposed. The new model introduces the notion of users’ behaviour into RBAC and provides means to influence users’ incentives. It is shown how RBAC policy can be used to individualise the cost of access to resources and also to determine users’ budget. The implementation overheads of B-RBAC is examined and several low-cost sub-models are proposed.

Designing a new robust on-line secondary path modeling technique for feedforward active noise control systems

Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.

A self-tuning feedforward active noise control system

This paper proposes a self-tuning feedforward active noise control (ANC) system with online secondary path modeling. The step-size parameters of the controller and modeling filters have crucial rule on the system performance. In literature, these parameters are adjusted by trial-and-error. In other words, they are manually initialized before system starting, which require performing extensive experiments to ensure the convergence of the system. Hence there is no guarantee that the system could perform well under different situations. In the proposed method, the appropriate values for the step-sizes are obtained automatically. Computer simulation results indicate the effectiveness of the proposed method.

An efficient online secondary path estimation for feedback active noise control systems

In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.

Situational non-flammable control valves for oxygen service

Past work has clearly demonstrated that numerous commonly used metallic materials will support burning in oxygen, especially at higher pressures. An approach to rectify this significant safety problem has been successfully developed and implemented by applying the concept of Situational Non-Flammability. This approach essentially removes or breaks one leg of the conceptual fire triangle, a tool commonly used to define the three things that are required to support burning; a fuel, an ignition source and an oxidizer. Since an oxidiser is always present in an oxygen system as are ignition sources, the concept of Situational Non-Flammability essentially removes the fuel leg of the fire triangle by only utilising materials that will not burn at the maximum pressure, for example, that the control valve is to be used in. The utilisation of this approach has lead to the development of a range of oxygen components that are practically unable to burn while in service at their design pressure thus providing an unparalleled level of first safety while not compromising on the performance or endurance required in the function of these components. This paper describes the concept of Situational Non-Flammability, how it was used to theoretically evaluate designs of components for oxygen service and the outcomes of the actual development, fabrication and finally utilisation of these components in real oxygen systems in a range of flow control devices.

What relationships exist between general self efficacy, locus of control and the nursing practice environment and caring efficacy and job satisfaction?

Research Question: What relationships exist between general self efficacy, locus of control and the nursing practice environment and caring efficacy and job satisfaction? Background: Important characteristics of current nursing practice include nurses having the ability to develop and continue therapeutic relationships with patients, nurses having autonomy and control over the practice environment and nurses having more involvement in decision making. In addition, employee satisfaction is enhanced when organisations offer access to authority. Despite this, nurses continue to complain of feeling powerless in their ability to make decisions. Sample: The study population and criteria for selection included Registered Nurses in Australia who were at the time members of an Australian professional and industrial organisation. Methods: A cross-sectional survey was undertaken. Data analysis was conducted using descriptive and bivariate statistics, and structural equation modeling. Results: The model fit the data well (χ² = 2.3594, χ²/df = 2.3594 and CFI = 0.9987). Twenty four percent of variation in caring efficacy (CE) can be accounted for by general self-efficacy (GSE); work locus of control (WLC) and practice environment (PE) and 62% of the variation in job satisfaction (JS) can be accounted for by GSE, WLC and PE. All pathways were found to be significant except PE to CE. GSE positively explained CE (β = 0.38). WLC was negatively related to CE i.e., as CE scores increased WLC scores decreased (β = -0.23). Further testing of the model found CE was positively related to GSE (βZ = 0.38, p < 0.001) and negatively related to WLC (βZ = - 0.23, p = 0.001). PE was not significantly associated with CE (βZ = - 0.01, p = 0.85). JS was explained by PE, which was positively related (βZ = 0.69, p = < 0.001); GSE which was negatively related (βZ - 0 .09, p < 0.001) and WLC, which was also negatively related (βZ = - 0.20, p < 0.001). Implications for Practice Nursing and organisational leaders should ensure the development of strategies for professional development and orientation programmes which may enhance nurses’ ability to develop caring relationships and express caring behaviours to their patients and as a result improve organisational and patient outcomes. Nursing shortages and turnover rates are associated with job satisfaction and the nursing practice environment. Improving the nursing environment can produce benefits to the health system such as better job satisfaction, improved workforce retention and better patient outcomes.

Comparison of two suspension control strategies for multi-axle heavy truck

Two simple and effective control strategies for a multi-axle heavy truck, modified skyhook damping (MSD) control and proportional-integration-derivative (PID) control, were implemented into functional virtual prototype (FVP) model and compared in terms of road friendliness and ride comfort. A four-axle heavy truck-road coupling system model was established using FVP technology and validated through a ride comfort test. Then appropriate passive air suspensions were chosen to replace the rear tandem suspensions of the original truck model for preliminary optimization. The mechanical properties and time lag of dampers were taken into account in simulations of MSD and PID semi-active dampers implemented using MATLAB/Simulink. Through co-simulations with Adams and MATLAB, the effects of semi-active MSD and PID control were analyzed and compared, and control parameters which afforded the best comprehensive performance for each control strategy were chosen. Simulation results indicate that compared with the passive air suspension truck, semi-active MSD control improves both ride comfort and road-friendliness markedly, with optimization ratios of RMS vertical acceleration and RMS tyre force ranging from 10.1% to 44.8%. However, semi-active PID control only reduces vertical vibration of the driver’s seat by 11.1%, 11.1% and 10.9% on A, B and C level roads respectively. Both strategies are robust to the variation of road level.

Optimized strategy for integrated traffic and transit signal control

This paper proposes a unique and innovative approach to integrate transit signal priority control into a traffic adaptive signal control strategy. The proposed strategy was named OSTRAC (Optimized Strategy for integrated TRAffic and TRAnsit signal Control). The cornerstones of OSTRAC include an online microscopic traffic f low prediction model and a Genetic Algorithm (GA) based traffic signal timing module. A sensitivity analysis was conducted to determine the critical GA parameters. The developed traffic f low model demonstrated reliable prediction results through a test. OSTRAC was evaluated by comparing its performance to three other signal control strategies. The evaluation results revealed that OSTRAC efficiently and effectively reduced delay time of general traffic and also transit vehicles.

QoS differentiation in IEEE 802.11 wireless local area networks for real-time control

IEEE 802.11 based wireless local area networks (WLANs) are being increasingly deployed for soft real-time control applications. However, they do not provide quality-ofservice (QoS) differentiation to meet the requirements of periodic real-time traffic flows, a unique feature of real-time control systems. This problem becomes evident particularly when the network is under congested conditions. Addressing this problem, a media access control (MAC) scheme, QoS-dif, is proposed in this paper to enable QoS differentiation in IEEE 802.11 networks for different types of periodic real-time traffic flows. It extends the IEEE 802.11e Enhanced Distributed Channel Access (EDCA) by introducing a QoS differentiation method to deal with different types of periodic traffic that have different QoS requirements for real-time control applications. The effectiveness of the proposed QoS-dif scheme is demonstrated through comparisons with the IEEE 802.11e EDCA mechanism.

A proposed Australian industrial control system security curriculum

The security of industrial control systems in critical infrastructure is a concern for the Australian government and other nations. There is a need to provide local Australian training and education for both control system engineers and information technology professionals. This paper proposes a postgraduate curriculum of four courses to provide knowledge and skills to protect critical infrastructure industrial control systems. Our curriculum is unique in that it provides security awareness but also the advanced skills required for security specialists in this area. We are aware that in the Australian context there is a cultural gap between the thinking of control system engineers who are responsible for maintaining and designing critical infrastructure and information technology professionals who are responsible for protecting these systems from cyber attacks. Our curriculum aims to bridge this gap by providing theoretical and practical exercises that will raise the awareness and preparedness of both groups of professionals.

Tipping the balance : sclerotinia sclerotiorum secreted oxalic acid suppresses host defenses by manipulating the host redox environment

Sclerotinia sclerotiorum is a necrotrophic ascomycete fungus with an extremely broad host range. This pathogen produces the non-specific phytotoxin and key pathogenicity factor, oxalic acid (OA). Our recent work indicated that this fungus and more specifically OA, can induce apoptotic-like programmed cell death (PCD) in plant hosts, this induction of PCD and disease requires generation of reactive oxygen species (ROS) in the host, a process triggered by fungal secreted OA. Conversely, during the initial stages of infection, OA also dampens the plant oxidative burst, an early host response generally associated with plant defense. This scenario presents a challenge regarding the mechanistic details of OA function; as OA both suppresses and induces host ROS during the compatible interaction. In the present study we generated transgenic plants expressing a redox-regulated GFP reporter. Results show that initially, Sclerotinia (via OA) generates a reducing environment in host cells that suppress host defense responses including the oxidative burst and callose deposition, akin to compatible biotrophic pathogens. Once infection is established however, this necrotroph induces the generation of plant ROS leading to PCD of host tissue, the result of which is of direct benefit to the pathogen. In contrast, a non-pathogenic OA-deficient mutant failed to alter host redox status. The mutant produced hypersensitive response-like features following host inoculation, including ROS induction, callose formation, restricted growth and cell death. These results indicate active recognition of the mutant and further point to suppression of defenses by the wild type necrotrophic fungus. Chemical reduction of host cells with dithiothreitol (DTT) or potassium oxalate (KOA) restored the ability of this mutant to cause disease. Thus, Sclerotinia uses a novel strategy involving regulation of host redox status to establish infection. These results address a long-standing issue involving the ability of OA to both inhibit and promote ROS to achieve pathogenic success.

A variable step-size FxLMS algorithm for feedforward active noise control systems based on a new online secondary path modelling technique

Several approaches have been introduced in literature for active noise control (ANC) systems. Since FxLMS algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANC applications an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. This paper also proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Benefiting new version of FxLMS algorithm and not continually injection of white noise makes the system more desirable and improves the noise attenuation performance. Comparative simulation results indicate effectiveness of the proposed approach.

A new online secondary path modelling method for feedforward active noise control systems

An online secondary path modelling method using a white noise as a training signal is required in many applications of active noise control (ANC) to ensure convergence of the system. Not continually injection of white noise during system operation makes the system more desirable. The purposes of the proposed method are two folds: controlling white noise by preventing continually injection, and benefiting white noise with a larger variance. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. This paper proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. Comparative simulation results shown in this paper indicate effectiveness of the proposed approach in controlling active noise.